A hitter will naturally lose approx. 10% of his hitting due to the fact he will face stronger opposition in a 20/24 team league. So that .320 hitter is more likely a .288 hitter with standard variable fluctuation. Using a 20% variance(which isn't dramatic), the hitter could then hit between .230 and .345. If you ran a 10 simulations, you might end up with a .230, .245,.260,.270,.280,.290,.300,.320,.325,.345 as his 10 seasons. Add them all up, you end up with 6000 atbats and a .290 ave.


I've never seen that huge of change for one pitcher, and don't know what stadium, what league, opposition faced, etc, he was in; plus it was real time, which throws additional variance.

For a 2.5 ERA guy, I'd predict a ERA in a 20 team replay to be approx 3.25. Pitchers have a higher variation, up to 50%. Pitching varies even more than hitting due to platoon lineups, type of defense behind the pitcher, pitchers going when they are tired, being left in the game longer than they should, etc. Additionally you have the lefty effect, which might add another 1/2 run. So I could see Johnson haveing an ERA of 3.75 ± 1.5 runs before park effects were taken into consideration.

I'm also in a DMB league, and have run many season long simulations, mainly becuase I heard that DMB was the most statistically accurate game on the market, even employed by ESPN. I also like the fact I can reproduce a whole season in 10 minutes. You get the same type of fluctuation with that game as you do here.

Every year, you will end up with about 2 hitters/pitchers doing better, 3 doing the same, and 5 doing worse. This is a given. Until we have a 1600 game season, it will always be this way.

Thankfully it is this way. If it wasn't, there would be no reason to play the games, because you could figure out how many games each team will win. Its the variation that allows a slightly inferior team to win a World Series....Just ask the Marlins and the Yankees about that.